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Writing concurrent programs is highly error-prone due to the nondeterminism in interprocess communication. The most reliable indicators of errors in concurrency are data races, which are accesses to a shared resource that can be executed…

Predictive data race detectors find data races that exist in executions other than the observed execution. Smaragdakis et al. introduced the causally-precedes (CP) relation and a polynomial-time analysis for sound (no false races)…

Dynamic data race prediction aims to identify races based on a single program run represented by a trace. The challenge is to remain efficient while being as sound and as complete as possible. Efficient means a linear run-time as otherwise…

Dynamic data race detection has emerged as a key technique for ensuring reliability of concurrent software in practice. However, dynamic approaches can often miss data races owing to nondeterminism in the thread scheduler. Predictive race…

The consequences of data races can be potentially very problematic [1], and it is important to determine what tools and methods are best at detecting them. The following conditions must be met for a data race to occur: two or more threads…

With the proliferation of multi-core hardware, parallel programs have become ubiquitous. These programs have their own type of bugs known as concurrency bugs and among them, data race bugs have been mostly in the focus of researchers over…

We consider the problem of detecting data races in program traces that have been compressed using straight line programs (SLP), which are special context-free grammars that generate exactly one string, namely the trace that they represent.…

Dynamic race detection is the problem of determining if an observed program execution reveals the presence of a data race in a program. The classical approach to solving this problem is to detect if there is a pair of conflicting memory…

Sound static analysis can prove the absence of data races by establishing that no two conflicting memory accesses can occur at the same time. We repurpose the concept of digests -- summaries of computational histories originally introduced…

Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur performance costs that are acceptable for regular in-house testing, but miss races detectable from the analyzed execution. Predictive analyses detect…

Data races are critical issues in multithreaded program, leading to unpredictable, catastrophic and difficult-to-diagnose problems. Despite the extensive in-house testing, data races often escape to deployed software and manifest in…

Monitoring concurrent programs typically rely on collecting traces to abstract program executions. However, existing approaches targeting general behavioral properties are either not tailored for online monitoring, are no longer maintained,…

Although automatic pathological speech detection approaches show promising results when clean recordings are available, they are vulnerable to additive noise. Recently it has been shown that databases commonly used to develop and evaluate…

Writing reliable concurrent software remains a huge challenge for today's programmers. Programmers rarely reason about their code by explicitly considering different possible inter-leavings of its execution. We consider the problem of…

Happens before-based dynamic analysis is the go-to technique for detecting data races in large scale software projects due to the absence of false positive reports. However, such analyses are expensive since they employ expensive vector…

Dynamic race detection based on the happens before (HB) partial order has now become the de facto approach to quickly identify data races in multi-threaded software. Most practical implementations for detecting these races use timestamps to…

Parallelism is often required for performance. In these situations an excess of non-determinism is harmful as it means the program can have several different behaviours or even different results. Even in domains such as high-performance…

Programmers of distributed systems need to reason about concurrency to avoid races. However, reasoning about concurrency is difficult, and unexpected races show up as bugs. Data race detection in shared memory systems is well-studied…

Happens-before based data race prediction methods infer from a trace of events a partial order to check if one event happens before another event. If two two write events are unordered, they are in a race. We observe that common tracing…

Dynamic data race detectors are indispensable for flagging concurrency errors in software, but their high runtime overhead limits their adoption. This overhead stems primarily from pervasive instrumentation of memory accesses - a…